Perfect Essay Writing

Research analysis Give an annotated summary (max 100 words) for each one: (bullet point for answers.

Order ready-to-submit essays. No Plagiarism Guarantee!

Note:  All our papers are written from scratch by human writers to ensure authenticity and originality.

Research analysis

Check your essay before you submit. See exactly what your professor sees.

See your AI and plagiarism results before your instructor does.Get the exact same report your professor uses. Trusted by 50,000+ students worldwide.

Give an annotated summary (max 100 words) for each one: (bullet point for answers

What is the main hypothesis?
Why is this research important?
How was the research question studied (provide paradigm)?
Observation, survey, case study, experiment, etc.
What were the variables in the study?
What statistical tests were conducted?
What was the key finding of the research?
What are the conclusions and limitations?
Why is this work relevant for your group work?

BRIEF REPORT
Concreteness effects in bilingual and monolingual
word learning
Margarita Kaushanskaya & Katrina Rechtzigel
Published online: 26 May 2012

Psychonomic Society, Inc. 2012

Abstract Previous studies have demonstrated that bilingualism
can facilitate novel-word learning. However, the mechanisms
behind this bilingual advantage remain unknown. Here,
we examined whether bilinguals may be more sensitive to
semantic information associated with the novel words. To that
end, we manipulated the concreteness of the referent in the
word-learning paradigm, since concrete words have been
shown to activate the semantic system more robustly than
abstract words do. The results revealed that the bilingual
advantage was stronger for novel words learned in association
with concrete rather than abstract referents. These findings
suggest that bilingual advantages for word learning may be
rooted, at least in part, in bilinguals’ greater sensitivity to
semantic information during learning.
Keywords Human memory and learning . Bilingualism .
Word meaning . Phonology . Semantics
Previous studies have suggested that bilingualism can facilitate
performance on word-learning tasks (e.g., Kaushanskaya
& Marian, 2009; Papagno & Vallar; 1995; Van Hell & Mahn,
1997). However, the mechanisms that underlie the effects of
bilingualism on learning are currently unknown. One early
suggestion was that the bilingual advantage for word learning
was based in bilinguals’ more efficient phonological memory
system (e.g., Papagno & Vallar, 1995). However, in recent
work we have shown that bilingual advantages for novel word
learning are maintained when bilingual and monolingual participants
are matched precisely on their phonological memory
capacity (Kaushanskaya, in press). Therefore, it is likely that
bilingual experience affects the learning process itself, rather
than (or in addition to) the cognitive workspace (i.e., the
working memory) within which learning takes place.
Although learning a word involves encoding both its phonological
form and its meaning, and although learning can
occur in a number of different ways, previous studies that
examined the effects of bilingualism on word learning have
typically used the paired-associates learning paradigm (rather
than other types of word-learning paradigms) and probed for
participants’ ability to retrieve the native-language translations
as the index of learning (e.g., Kaushanskaya, in press;
Kaushanskaya & Marian, 2009; Van Hell & Mahn, 1997). A
promising clue to how bilingualism may influence this particular
word-learning process was yielded by analyses of wordlearning
errors made by bilingual versus monolingual learners
(Kaushanskaya & Rechtzigel, 2012). In this previous study,
participants were taught to associate novel words with English
translations, and at testing, they were asked to produce the
English translations when cued with the novel words. While a
general pattern of bilingual advantages was uncovered, more
interesting findings were observed when translation errors
were analyzed. Errors were coded into two categories:
sound-based errors (in which participants confused two
similar-sounding novel words) and meaning-based errors (in
which participants confused two English translations that
shared a semantic category or that were associatively related
to each other). The analyses of errors were conducted on the
proportion data (e.g., on the number of sound-based errors out
of the total number of errors) to correct for the fact that
bilinguals made fewer errors overall than did monolinguals.
When analyzed in this way, bilinguals made more meaningbased
errors than did monolinguals. These results were
Electronic supplementary material The online version of this article
(doi:10.3758/s13423-012-0271-5) contains supplementary material,
which is available to authorized users.
M. Kaushanskaya () : K. Rechtzigel Department of Communicative Disorders, University of Wisconsin–Madison, 1975 Willow Drive, Madison, WI 53706, USA e-mail: kaushanskaya@wisc.edu Psychon Bull Rev (2012) 19:935–941 DOI 10.3758/s13423-012-0271-5 interpreted to suggest that given the same task parameters and stimuli, bilinguals may be able to encode novel words more deeply (i.e., to the semantic level) than do monolinguals. The goal of the present study was to experimentally assess whether this was the case. We asked: Are bilinguals more sensitive to the semantic information associated with novel words during learning than are monolinguals? In order to examine whether bilinguals and monolinguals differ in how they process semantic information during learning, we contrasted the learning of novel words in association with concrete versus abstract referents. In memory tasks, concreteness effects have been broadly confirmed (e.g., Hamilton & Rajaram, 2001; Miller & Roodenrys, 2009; Romani, McAlpine, & Martin, 2008; Walker & Hulme, 1999) using both paired-associates learning (e.g., Gee, Nelson, & Krawczyk, 1999) and novel-word learning paradigms (e.g., De Groot & Keijzer, 2000). Although the roots of concreteness effects continue to be debated, nearly all memory/learning studies that contrast concrete versus abstract words have revealed better performance on concrete words (e.g., De Groot & Keijzer, 2000; Hamilton & Rajaram, 2001; Miller & Roodenrys, 2009; Romani et al., 2008; Walker & Hulme, 1999), and all of the theoretical explanations for why concrete words are advantaged during processing entail semantic (rather than phonological) differences between concrete and abstract words. Thus, some studies have indicated that concrete words are processed by both the verbal and the image-based systems, while abstract words activate the verbal system only (Paivio, 1986, 1991; Paivio, Walsh, & Bons, 1994). Others have argued that concreteness effects are due to richer semantic representations (which may involve a wider network of prior contextual knowledge) for concrete words (e.g., De Groot, 1989; Grondin, Lupker, & McRae, 2009; Schwanenflugel & Shoben, 1983). For the purposes of the present study, we assumed that the ease associated with retaining concrete words is rooted in semantic factors. We therefore hypothesized that if bilinguals were more sensitive to semantic information during learning than monolinguals, the bilingual advantage for novel-word learning would be especially strong for concrete words. The comparison of bilinguals and monolinguals on learning tasks contrasting the learning of novel words in association with concrete versus abstract referents also enabled us to examine the strength of concreteness effects in the two groups of learners. Theories of lexical processing in bilinguals generally posit that the semantic representations of translation equivalents in a bilingual’s two languages overlap (e.g., Kroll & Stewart, 1994). However, there have also been suggestions that different types of words overlap in the bilingual semantic system to different degrees. Specifically, the distributed feature model (De Groot, 1992) posits that concrete words are more likely to share semantic features across bilinguals’ two languages than are abstract words, and some behavioral evidence has suggested that concrete translation pairs across the bilingual’s two languages may share a larger semantic overlap than do abstract translation pairs (e.g., Jin, 1990; Paivio & Desrochers, 1980; Van Hell & De Groot, 1998). As a result, bilinguals tend to translate concrete words more quickly than abstract words (De Groot, Dannenburg, & Van Hell, 1994; De Groot & Poot, 1997; but see Tokowicz & Kroll, 2007, for an alternative explanation). Using the distributed feature model as the framework, it is possible to generate specific predictions with regard to the strengths of the concreteness effects in bilingual versus monolingual learning. In monolinguals, presentation of a concrete word activates a wider lexical–semantic network than does the presentation of an abstract word (e.g., De Groot, 1989; Grondin et al., 2009; Schwanenflugel & Shoben, 1983), and the same is likely true for bilingual speakers. However, presentation of a concrete item in one of the bilinguals’ two languages is likely to activate a wider lexical–semantic network than does the presentation of the same item to a monolingual, because in a bilingual, activation will include both the language in which the word was presented and the other language. Conversely, presentation of an abstract item in one of the bilingual’s two languages is likely to activate a network similar to that in a monolingual speaker, since abstract translation equivalents do not overlap in the semantic network of a bilingual speaker to the same extent as concrete translation equivalents. If activation of the lexical–semantic system is stronger for concrete than for abstract words, and if bilinguals’ lexical–semantic system is more robustly activated in response to the concrete words, then concreteness effects should be larger for bilingual than for monolingual learners. Method Participants A group of 44 participants completed the study. Of these, 22 participants were monolingual native speakers of English who reported no significant knowledge of a second language (defined as self-ratings of second-language [L2] speaking proficiency of 2 or less on a scale from 0 [no knowledge] to 10

[native-like knowledge]

), and 22 were English–Spanish bilinguals. The bilingual participants were carefully screened to ensure the following: English as the native language, selfrated average proficiency in Spanish of 7 or above (averaged across speaking and understanding ratings), and at least one immersion experience of at least 2 months in length in a Spanish-speaking country or family. Upon selection, bilingual participants were also administered a standardized receptive vocabulary test in Spanish in order to ensure adequate levels of Spanish knowledge. The demographic characteristics of the bilingual participants are reported in Table 1. All the demographic and language experience information was collected 936 Psychon Bull Rev (2012) 19:935–941 using the Language Experience and Proficiency Questionnaire (Marian, Blumenfeld, & Kaushanskaya, 2007). Although bilingual and monolingual participants were recruited from the same college-student population of the University of Wisconsin–Madison, the requirement for immersion experience in the bilingual group resulted in slightly unbalanced groups (see Table 2). Specifically, bilinguals were on average 1.87 years older than the monolinguals, with 1.64 more years of education. The two groups were matched in English receptive vocabulary skills and in verbal working memory skills. All participants were screened for nonverbal intelligence to ensure within-normal cognitive skills. Raw scores on the Kaufman Brief Intelligence Test–II were comparable between the two groups (p 0 .17). However, when raw scores were transformed into standard scores, the age difference between the two groups resulted in the hypercorrection of the bilinguals’ scores. The result of this hypercorrection was a significant difference between bilinguals’ and monolinguals’ standard IQ scores. Materials Two lists of 12 novel words were selected from the Gupta et al. (2004) nonword database. All novel words were two syllables in length and followed the sound patterns of English (e.g., gapume, botefe). None of the novel words were real words in Spanish. The stimuli were matched across the two lists on syllable structure, in that all novel words were consonant–vowel–consonant–vowel–consonant pseudowords. The novel words across the two lists did not differ in duration [List A, M 0 999.17 ms, SD 0 69.05; List B, M 0 1,015.67 ms, SD 0 81.00; t(11) 0 0.62, p 0 .55], phonotactic probability [List A 0 0.23, SD 0 0.04; List B 0 0.23, SD 0 0.04; t(11) 0 0.33, p 0 .75], or biphone frequency [List A 0 0.007, SD 0 0.003; List B 0 0.007, SD 0 0.04; t(11) 0 0.62, p 0 .55]. The phonotactic and biphone frequency values were calculated using the phonotactic probability calculator (Vitevitch & Luce, 2004). The two lists of nonword stimuli can be found in supplementary materials for this article. Each novel word was paired with an English word. One list of novel words was paired with concrete English nouns (e.g., daisy, helmet), and the other list of novel words was paired with abstract English nouns (e.g., virtue, sorrow). The pairing of novel-word lists with English noun lists (concrete vs. abstract) was counterbalanced across participants. Concreteness was determined using the MRC lexical database. Only nouns with concreteness ratings above 500 (on a scale from 100 to 700) were selected for the concrete list, and only nouns with concreteness ratings below 350 were selected for the abstract lists. The two lists of English words (concrete vs. abstract) differed significantly in their concreteness ratings (concrete, M 0 588.67, SD 0 24.60; abstract, M 0 279.42, SD 0 31.74) [t(11) 0 29.81, p <> However, the two lists of English words were matched on syllable length, frequency of use [concrete, M 0 36.16, SD 0 40.79; abstract, M 0 37.50, SD 0 43.39; t(11) 0 1.07, p 0 .31], phonotactic probability [concrete, M 0 0.28, SD 0 0.10; abstract, M 0 0.30, SD 0 0.13; t(11) 0 0.45, p 0 .66], biphone frequency [concrete, M 0 0.02, SD 0 0.01; abstract, M 0 0.02, SD 0 0.02; t(11) 0 0.49, p 0 .63], and number of lexical neighbors [concrete, M 0 0.75, SD 0 1.14; abstract, M 0 1.00, SD 0 2.59; t(11) 0 0.29, p 0 .77]. Frequency of use (per million) and neighborhood density values were calculated using CELEX (Baayen, Piepenbrock, & Gulikers, 1995). The novel words and the English words were recorded by two different female speakers, both of whom were native speakers of American English. All stimuli were recorded in a soundproof booth at a 44-kH sampling rate and were normalized to 70-dB amplitude using Praat (Boersma & Weenink, 2007). Table 1 Spanish (L2) acquisition and L2 use data for bilingual participants (means and SDs) L2 Data Mean (SD) Test de Vocabulario en Imagenes de Peabody (standard score) 113.30 (4.10) Age of L2 acquisition 9.50 (4.80) Degree of current L2 exposure 8.70 % (6.50) Self-rated L2 proficiency: Speaking (0–10 scale) 7.50 (0.90) Self-rated L2 proficiency: Understanding (0–10 scale) 8.10 (1.10) Years of immersion in a Spanish-speaking country 1.50 (3.60) Table 2 Monolingual and bilingual participants data (means and SDs) Monolinguals (n022) Bilinguals (n022) t Value Age 20.07 (1.0) 21.94 (1.8) 4.34
Years of education 14.6 (1.0) 16.3 (1.3) 4.37*
Peabody Picture
Vocabulary Test–III
(standard scores)
111.5 (4.4) 116.6 (13.3) 2.57
Woodcock Johnson Tests
of Cognitive Abilities–II
Numbers Reversed
(standard scores)
109.8 (12.7) 113.8 (10.8) 1.11
Kaufman Brief
Intelligence Test–II
Visual Matrices
(raw scores)
38.77 (0.72) 40.45 (0.95) 1.41
Kaufman Brief
Intelligence Test–II
Visual Matrices
(standard scores)
103.45 (2.13) 111.55 (2.80) 2.27*

  • Significant differences between monolinguals and bilinguals, p <>
    Psychon Bull Rev (2012) 19:935–941 937
    Procedure
    Each participant completed the entire experiment in a single
    testing session. During the learning phase, novel words and
    their English translations were presented over computer
    speakers in a soundproof booth. The novel word was always
    presented first, followed by the English word. The presentation
    of concrete and abstract pairs was intermixed. Each
    pair was presented twice during the learning phase, with the
    order of presentation randomized for each participant. The
    interstimulus interval between the presentation of the novel
    word and its English translation was set to 750 ms, and the
    interval between presentations of the pairs was set to 3 s.
    Participants were instructed to memorize the association
    between the novel words and their English translations.
    During the testing phase, participants were asked to produce
    the correct English translations for the novel words.
    Such translation-like tasks are common measures of associative
    learning (e.g., De Groot & Keijzer, 2000; Paivio &
    Yuille, 1969) and have frequently been used in previous
    studies of novel-word learning with both bilinguals and
    monolinguals (e.g., Kaushanskaya & Marian, 2009; Van
    Hell & Mahn, 1997). Each novel word was played over
    speakers, and the participants were instructed to produce
    the corresponding English translation into a microphone.
    The responses were recorded as sound files for later coding
    and analyses.
    During the standardized testing phase, standardized
    language and intelligence tests were administered to
    each participant, including an English receptive vocabulary
    test (Peabody Picture Vocabulary Test–III), a nonverbal
    IQ test (Kaufman Brief Intelligence Test, Visual
    Matrices subtest), and a verbal working memory test
    (Numbers Reversed subtest of the Woodcock Johnson
    Tests of Cognitive Abilities–II). A measure of Spanish receptive
    vocabulary was administered to the bilingual speakers
    (Test de Vocabulario en Imágenes de Peabody).
    Analyses
    The production accuracy data (proportions correct) were
    normally distributed (Kolmogorov–Smirnov statistics
    < 0.15,=”” p=””>.1), and therefore were analyzed using a 2 ×
    2 ANOVA, with group (monolingual vs. bilingual) and concreteness
    (concrete vs. abstract) as independent variables.
    Both by-subjects (F1) and by-items (F2) analyses are reported.
    Production reaction time (RT) data were also analyzed using a
    2 × 2 ANOVA. RTs were measured from the onset of the novel
    word to the participant’s buttonpress after production of the
    English translation. Only RTs for the correctly produced translations
    were included in the calculations of mean RTs. Years of
    education and standard scores on the nonverbal IQ measure
    were covaried out in all of the cross-group by-subjects
    analyses. Age was not covaried out, because it correlated
    highly with years of education.
    Results
    Accuracy analyses
    The proportion correct data across groups and conditions are
    presented in Fig. 1. A 2 × 2 ANOVA revealed a main effect
    of concreteness [F1(1, 41) 0 4.26, MSE 0 0.05, p <>
    ?p
    2 0 .10; F2(1, 22) 0 17.37, MSE 0 0.23, p <>
    ?p
    2 0 .44], with concrete referents (M 0 .22, SE 0 .02)
    retrieved more accurately than abstract referents (M 0 .11,
    SE 0 .02). The main effect of group was not significant in the
    by-subjects analysis [F1(1, 41) 0 2.38, MSE 0 0.02, p 0 .13,
    ?p
    2 0 .09], but was significant in the by-items analysis
    [F2(1, 22) 0 6.32, MSE 0 0.04, p < .05,=””>
    2 0 .22]. Bilinguals
    (M 0 .19, SE 0 .02) tended to outperform monolinguals
    (M 0 .13, SE 0 .03). Crucially, the interaction between concreteness
    and group was significant [F1(1, 41) 0 5.01, p < .05,=”” mse=””>
    0.06, ?p
    2 0 .12; F2(1, 22) 0 5.55, p < .05,=”” mse=”” 0=”” 0.04,=””>
    2 0 .11].
    Follow-up univariate ANOVAs with group as the independent
    variable revealed that bilingual participants were more
    accurate than monolingual participants when retrieving concrete
    referents for the newly learned words [F1(1, 42) 0 5.54,
    MSE 0 0.10, p < .05,=””>
    2 0 .12; F2(1, 11) 0 4.91,
    MSE 0 0.03, p < .05,=””>
    2 0 .31]. However, bilinguals and
    monolinguals were similarly accurate when retrieving abstract
    referents for the newly learned words [F1(1, 42) 0 0.19,
    MSE 0 0.01, p 0 .67, ?p
    2 0 .02; F2(1, 11) 0 1.70, MSE 0 0.01,
    p 0 .22, ?p
    2 0 .13].
    Follow-up repeated measures ANOVAs with concreteness
    as the independent variable were used to examine the
    strength of the concreteness effects within each group separately.
    These analyses revealed a significant concreteness
    effect in the bilingual group [F1(1, 21) 0 21.51,
    MSE 0 0.27, p < .001,=””>
    2 0 .51; F2(1, 22) 0 10.71,
    0
    0.1
    0.2
    0.3
    0.4
    0.5 Abstract Referents
    Concrete Referents
    Proportion Correct
    Monolinguals Bilinguals
    *
    *
    *
    Fig. 1 Mean monolingual and bilingual translation accuracy (proportions
    correct) in the concrete-referent and abstract-referent conditions.
    The error bars represent standard deviations. *
    p <>
    938 Psychon Bull Rev (2012) 19:935–941
    MSE 0 0.15, p < .01,=””>
    2 0 .33] and in the monolingual
    group [F1(1, 21) 0 8.57, MSE 0 0.11, p < .01,=””>
    2 0 .29;
    F2(1, 22) 0 14.27, MSE 0 0.09, p < .01,=””>
    2 0 .39]. However,
    comparisons of the effect sizes in the by-subjects data
    revealed that the effect of concreteness was significantly
    stronger in the bilingual group than in the monolingual group,
    z score 0 12.96, p <>
    RT analyses
    A 2 × 2 ANOVA revealed a marginally significant effect of
    concreteness in the by-subjects analyses [F1(1, 23) 0 4.06,
    MSE 0 40,533,371.77, p 0 .056, ?p
    2 0 .15], but not in the
    by-items analyses [F2(1, 18) 0 0.00, MSE 0 0.13, p 0 .10,
    ?p
    2 < .001].=”” there=”” was=”” a=”” tendency=”” for=”” concrete=”” referents=”” (m=””>
    5,108.58, SE 0 677.95) to be retrieved more quickly than
    abstract referents (M 0 6,922.43, SE 0 514.37). The main
    effect of group was not significant [F1(1, 23) 0 0.29, MSE 0
    2,242,493.76, p 0 .60, ?p
    2 0 .01; F2(1, 18) 0 0.002, MSE 0
    9,709.26, p 0 .96, ?p
    2 < .001].=”” moreover,=”” the=””>
    between concreteness and group was also not significant
    [F1(1, 23) 0 2.80, MSE 0 27,903,646.31, p 0 .11, ?p
    2 0 .11;
    F2(1, 18) 0 2.75, MSE 0 11,677,855.14, p 0 .12, ?p
    2 0 .13].
    Discussion
    In the present study, we contrasted the learning of novel words
    in association with concrete versus abstract English translations
    in order to test the hypothesis that the bilingual advantages
    for novel-word learning may be based, at least in part, on
    bilinguals’ sensitivity to the semantic information associated
    with the novel words. Prior extensive work on concreteness
    effects strongly supports semantic differences between abstract
    and concrete words (De Groot, 1989; Grondin et al.,
    2009; Paivio, 1986, 1991; Paivio et al., 1994; Schwanenflugel
    & Shoben, 1983), with concrete words activating a richer
    network of semantic information (e.g., mental imagery or a
    wider network of contextual information) than abstract words.
    Our finding of a stronger bilingual advantage for concrete than
    for abstract novel words suggests that the effects of bilingualism
    on word learning are more likely to emerge when semantic
    information associated with the novel words is more
    accessible. The lack of significant RT differences between
    bilinguals and monolinguals on the translation task indicates
    that bilinguals’ more accurate translation performance was not
    a result of accuracy–RT trade-offs or of bilinguals’ strategic
    allocation of time to the translation task.
    What may explain the bilinguals’ superior learning of
    concrete words? Consideration of concreteness effects in the
    monolingual group versus the bilingual group is helpful in
    informing this question. Although a main effect of concreteness
    was found, it is apparent that concreteness effects were
    stronger in the bilingual group than in the monolingual group.
    The difference between the concrete and abstract conditions in
    the bilingual group (mean difference 0 .17) was more than
    twice the size of the difference in the monolingual group
    (mean difference 0 .08). Previous work on the representations
    of concrete versus abstract words in the bilingual lexical–
    semantic system suggests that concrete translation pairs across
    bilinguals’ two languages may share a larger semantic overlap
    than do abstract translation pairs (e.g., De Groot, 1992; Jin,
    1990; Paivio & Desrochers, 1980; Van Hell & De Groot,
    1998). Therefore, it is possible that concrete words cause a
    wider activation of the bilingual lexical–semantic system (vs.
    the monolingual system), thus yielding a stronger concreteness
    effect in bilinguals than in monolinguals. It may be that
    the same mechanism—namely, the structure of the bilingual
    (vs. the monolingual) lexical–semantic system—is what drove
    the stronger bilingual advantage for the concrete than for the
    abstract words. The English translations would have activated
    a wider lexical–semantic network in bilinguals than in monolinguals,
    since in bilinguals the activation would have involved
    both the activation of the English lexical–semantic
    network and the overlapping Spanish lexical–semantic network.
    This would result in more robust lexical–semantic
    activation in response to concrete words in bilinguals, thus
    yielding stronger learning. Conversely, abstract English translations
    would have activated similar lexical–semantic networks
    in bilinguals and in monolinguals, yielding comparable learning
    profiles in the two groups of learners.
    Thus, it may be that sensitivity to semantic information
    during learning is a general property of the bilingual processing
    system, where through exposure to two languages,
    the bilingual’s semantic system becomes more interactive,
    especially when confronted with concrete stimuli. That is,
    bilingual advantages for the learning of concrete words may
    stem not from different learning mechanisms in bilinguals
    versus monolinguals, but from the higher levels of semantic
    activation in the bilingual versus the monolingual lexical–
    semantic system, as a result of the availability of two languages.
    Thus, bilingual advantages for novel-word learning
    may be a natural outcome of how words are stored and
    processed in the bilingual versus the monolingual lexical–
    semantic system. This explanation of bilingual advantages
    on word-learning tasks is theoretically akin to Gollan and
    colleagues’ (Gollan & Acenas, 2004; Gollan, Montoya,
    Fennema-Notestine, & Morris, 2005; Gollan & Silverberg,
    2001) explanation of bilingual disadvantages on wordprocessing
    tasks. Gollan et al. have suggested that bilinguals’
    reduced lexical retrieval abilities are an outcome not
    of fundamental differences in language processing between
    bilinguals and monolinguals, but of the fact that bilinguals,
    by virtue of distributed lexical exposure, have weaker links
    between lexical and semantic representations. Here, it is possible
    that bilinguals’ more efficient lexical learning is an
    Psychon Bull Rev (2012) 19:935–941 939
    outcome of a more resonant and interactive semantic system
    in bilinguals as a result of cross-linguistic coactivation.
    The stronger effect of bilingualism on the learning of
    concrete (rather than abstract) novel words, although suggestive
    of a mechanism that underlies bilingual advantages
    for word-learning tasks, leaves open a number of additional
    possibilities as to the identity of this mechanism. For example,
    it is possible that bilinguals may benefit from concrete
    referents because they recognize that focusing on the words’
    meanings would be a successful strategy on this particular
    type of learning task, and thus they choose to consciously
    employ this strategy. It may be feasible in future studies to
    examine whether bilinguals’ sensitivity to semantic information
    is an outcome of strategy use by instructing learners
    to use semantic versus rote (phonological) strategies when
    encoding novel words. If bilinguals are able to strategically
    allocate attention to the semantic information associated
    with the novel words, they should be particularly skilled at
    utilizing meaning-based strategies at learning, independent
    of the semantic content of the words (concrete or abstract).
    If, on the other hand, the interactivity of the bilingual
    lexical–semantic system is at the root of the bilingual advantages
    for learning concrete words, then manipulating learning
    strategy should not influence the patterns observed in
    the present study. That is, independent of how learners are
    instructed to learn, bilinguals would be expected to outperform
    monolinguals on the concrete but not on the abstract
    items.
    The interpretation of the bilingual advantage for word
    learning observed in the present study must be qualified by
    the following considerations. First, this word-learning task
    is well practiced by experienced learners. In fact, Van Hell
    and Mahn (1997) demonstrated that experienced language
    learners (i.e., multilingual learners with large amounts of
    classroom-based language-learning experience) were especially
    successful at learning novel words via a pairedassociates-learning-like
    method. Therefore, the finding of a
    bilingual advantage in the present study may apply only to
    bilinguals with vast amounts of L2 experience and to learning
    tasks of this particular kind. It is interesting to note that
    although our strict inclusion criteria for bilingual participants
    resulted in a homogeneous group of bilinguals with
    respect to their L2 proficiency, there was variability in the
    bilingual group with respect to the age at which the L2 was
    acquired. When bilingual participants’ word-learning data
    were correlated with L2 age-of-acquisition data, inverse
    correlations were observed between age of acquisition and
    translation accuracy. The correlation was significant for
    abstract words (r 0 –.45, p < .05),=”” but=”” not=”” for=”” concrete=””>
    (r 0 –.18, p 0 .42). The fact that earlier exposure to the L2
    was associated with better word-learning performance indicates
    that robust exposure to an L2 is likely to be crucial for
    the positive effects of bilingualism to emerge on learning
    tasks of the kind used in the present study. Second, the
    finding that the bilingual advantage for word-learning tasks
    is qualified by concreteness may be specific to retention
    measures that probe for the meanings associated with the
    novel words, as was the case in the present study. Therefore,
    it will be important to test both the retention of the novel
    word forms and of their meanings in the future. Third,
    although the translation accuracy rates in the present study
    were quite similar to those in other published accuracy data
    on translation-like tasks administered immediately after
    learning (e.g., Kaushanskaya, in press), they are suggestive
    of the high levels of difficulty associated with this particular
    learning task. Therefore, it is possible that bilingual advantages
    on learning tasks are especially likely to be observed
    when tasks are quite challenging.
    In conclusion, the goal of the present work was to inform
    the search for the mechanisms that may underlie the effects
    of bilingualism on learning. We found that the bilingual
    advantage was stronger for concrete than for abstract novel
    words, and we ascribe this advantage to bilinguals’ greater
    sensitivity to the semantic information associated with the
    novel words. It may be that the bilingual lexical–semantic
    system is more robustly activated in response to semantically
    rich material than is the monolingual lexical–semantic
    system, yielding stronger concreteness effects and better
    retention of concrete words in bilingual versus monolingual
    learners.
    Author note This research was supported in part by a University of
    Wisconsin–Madison Graduate School Research Committee WARF
    Grant to M.K. The authors thank Matt Goldrick, Nicolas Dumay, two
    anonymous reviewers, and the members of the Language Acquisition
    and Bilingualism Lab for their helpful suggestions on this manuscript,
    and the Study Abroad Office of the University of Wisconsin-Madison
    for their help with participant recruitment.
    References
    Baayen, R. H., Piepenbrock, R., & Gulikers L. (1995). The CELEX
    lexical database (Release 2). Philadelphia, PA: Linguistic Data
    Consortium, University of Pennsylvania.
    Boersma, P., & Weenink, D. (2007). Praat: Doing phonetics by computer
    (Version 4.6) [Computer program]. Retrieved from www.
    praat.org.
    De Groot, A. M. B. (1989). Representation aspects of word imageability
    and word frequency as assessed through word association.
    Journal of Experimental Psychology: Learning, Memory, and
    Cognition, 15, 824–845.
    De Groot, A. M. B. (1992). Determinants of word translation. Journal
    of Experimental Psychology: Learning, Memory, and Cognition,
    18, 1001–1018.
    De Groot, A. M. B., & Keijzer, R. (2000). What is hard to learn is easy
    to forget: The roles of word concreteness, cognate status, and
    word frequency in foreign-language vocabulary learning and forgetting.
    Language Learning, 50, 1–56.
    940 Psychon Bull Rev (2012) 19:935–941
    De Groot, A. M. B., & Poot, R. (1997). Word translation at three levels
    of proficiency in a second language: The ubiquitous involvement
    of conceptual memory. Language Learning, 47, 215–264.
    De Groot, A. M. B., Dannenburg, L., & Van Hell, J. G. (1994).
    Forward and backward word translation by bilinguals. Journal
    of Memory and Language, 33, 600–629.
    Gee, N. R., Nelson, D. L., & Krawczyk, D. (1999). Is the concreteness
    effect a result of underlying network connectivity? Journal of
    Memory and Language, 40, 479–497.
    Gollan, T. H., & Acenas, L. A. (2004). What is a TOT? Cognate and
    translation effects on tip-of-the-tongue states in Spanish–English
    and Tagalog–English bilinguals. Journal of Experimental Psychology:
    Learning, Memory, and Cognition, 30, 246–269. doi:10.1037/
    0278-7393.30.1.246
    Gollan, T. H., & Silverberg, N. B. (2001). Tip-of-the-tongue states in
    Hebrew–English bilinguals. Bilingualism: Language and Cognition,
    4, 63–83. doi:10.1017/S136672890100013X
    Gollan, T. H., Montoya, R. I., Fennema-Notestine, C., & Morris, S. H.
    (2005). Bilingualism affects picture naming but not picture classification.
    Memory & Cognition, 33, 1220–1234.
    Grondin, R., Lupker, S. J., & McRae, K. (2009). Shared features
    dominate semantic richness effects for concrete concepts. Journal
    of Memory and Language, 60, 1–19.
    Gupta, P., Lipinski, J., Abbs, B., Lin, P.-H., Aktunc, E., Ludden, D., . . .
    Newman, R. (2004). Space aliens and nonwords: Stimuli for
    investigating the learning of novel word–meaning pairs. Behavior
    Research Methods, Instruments, & Computers, 36, 599–603.
    doi:10.3758/BF03206540
    Hamilton, M., & Rajaram, S. (2001). The concreteness effect in implicit
    and explicit memory tests. Journal of Memory and Language, 44,
    96–117.
    Jin, Y.-S. (1990). Effects of concreteness on cross-language priming in
    lexical decision. Perceptual and Motor Skills, 70, 1139–1154.
    Kaushanskaya, M. (in press). Cognitive mechanisms of word learning
    in bilingual and monolingual adults: The role of phonological
    memory. Bilingualism: Language and Cognition. doi:10.1017/
    S1366728911000472
    Kaushanskaya, M., & Marian, V. (2009). The bilingual advantage in
    novel word learning. Psychonomic Bulletin & Review, 16, 705–710.
    Kaushanskaya, M., & Rechtzigel, K. (2012). What can errors tell us
    about differences between monolingual and bilingual word learning?
    Manuscript submitted for publication.
    Kroll, J. F., & Stewart, E. (1994). Category interference in translation
    and picture naming: Evidence for asymmetric connections between
    bilingual memory representations. Journal of Memory
    and Language, 33, 149–174.
    Marian, V., Blumenfeld, H. K., & Kaushanskaya, M. (2007). The
    Language Experience and Proficiency Questionnaire (LEAP-Q):
    Assessing language profiles in bilinguals and multilinguals. Journal
    of Speech, Language, and Hearing Research, 50, 940–967.
    Miller, L. M., & Roodenrys, S. (2009). The interaction of word
    frequency and concreteness in immediate serial recall. Memory
    & Cognition, 37, 850–865.
    Paivio, A. (1986). Mental representations. Oxford, U.K.: Oxford University
    Press.
    Paivio, A. (1991). Dual coding theory: Retrospect and current status.
    Canadian Journal of Psychology, 45, 255–287.
    Paivio, A., & Desrochers, A. (1980). A dual-coding approach to
    bilingual memory. Canadian Journal of Psychology, 34, 388–399.
    Paivio, A., & Yuille, J. C. (1969). Changes in associative strategies and
    paired-associate learning over trials as a function of word imagery
    and type of learning set. Journal of Experimental Psychology, 79
    (3, Pt. 1), 458–463. doi:10.1037/h0026929
    Paivio, A., Walsh, M., & Bons, T. (1994). Concreteness effects on
    memory: When and why? Journal of Experimental Psychology:
    Learning, Memory, and Cognition, 20, 1196–1204.
    Papagno, C., & Vallar, G. (1995). Verbal short-term memory and
    vocabulary learning in polyglots. Quarterly Journal of Experimental
    Psychology, 48A, 98–107.
    Romani, C., McAlpine, S., & Martin, R. C. (2008). Concreteness effects
    in different tasks: Implications for models of short-term memory.
    Quarterly Journal of Experimental Psychology, 61, 292–323.
    Schwanenflugel, P. J., & Shoben, E. J. (1983). Differential context
    effects in the comprehension of abstract and concrete materials.
    Journal of Experimental Psychology: Learning, Memory, and
    Cognition, 9, 82–102.
    Tokowicz, N., & Kroll, J. F. (2007). Number of meanings and concreteness:
    Consequences of ambiguity within and across languages.
    Language and Cognitive Process, 22, 727–779. doi:10.1080/
    01690960601057068
    Van Hell, J. G., & De Groot, A. M. B. (1998). Conceptual representation
    in bilingual memory: Effects of concreteness and cognate
    status in word association. Bilingualism: Language and Cognition,
    1, 193–211.
    Van Hell, J. G., & Mahn, A. C. (1997). Keyword mnemonics versus
    rote rehearsal: Learning concrete and abstract foreign words by
    experienced and inexperienced learners. Language Learning, 47,
    507–546.
    Vitevitch, M. S., & Luce, P. A. (2004). A Web-based interface to
    calculate phonotactic probability for words and nonwords in
    English. Behavior Research Methods, Instruments, and Computers,
    36, 481–487. doi:10.3758/BF03195594
    Walker, I., & Hulme, C. (1999). Concrete words are easier to recall
    than abstract words: Evidence for a semantic contribution to
    short-term serial recall. Journal of Experimental Psychology:
    Learning, Memory, and Cognition, 25, 1256–1271.
    Psychon Bull Rev (2012) 19:935–941 941
    Copyright of Psychonomic Bulletin & Review is the property of Springer Science & Business Media B.V. and
    its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder’s
    express written permission. However, users may print, download, or email articles for individual use.
SOURCE: WWW.ROYALRESEARCHERS.COM
Havent found the Essay You Want?
We Can Help
The Essay is Written From Scratch for You

🛒Place Your Order

ORDER AN ESSAY WRITTEN FROM SCRATCH at : https://royalresearchers.com/
PLACE YOUR ORDER
Share your love